Abstract
Computer science advances and ultra-fast computing speeds find artificial intelligence
(AI) broadly benefitting modern society—forecasting weather, recognizing faces, detecting
fraud, and deciphering genomics. AI's future role in medical practice remains an unanswered
question. Machines (computers) learn to detect patterns not decipherable using biostatistics
by processing massive datasets (big data) through layered mathematical models (algorithms).
Correcting algorithm mistakes (training) adds to AI predictive model confidence. AI
is being successfully applied for image analysis in radiology, pathology, and dermatology,
with diagnostic speed exceeding, and accuracy paralleling, medical experts. While
diagnostic confidence never reaches 100%, combining machines plus physicians reliably enhances system performance. Cognitive programs are impacting
medical practice by applying natural language processing to read the rapidly expanding
scientific literature and collate years of diverse electronic medical records. In
this and other ways, AI may optimize the care trajectory of chronic disease patients,
suggest precision therapies for complex illnesses, reduce medical errors, and improve
subject enrollment into clinical trials.
Keywords
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Article Info
Publication History
Published online: November 07, 2017
Footnotes
Funding: None.
Conflicts of Interest: DDM: None; EWB: Employed by IBM; the employment relationship did not create direct or indirect financial or scientific conflicts in the preparation of this paper.
Authorship: All authors had access to the data and a role in writing this manuscript.
Identification
Copyright
© 2018 Elsevier Inc. All rights reserved.
